The invention relates to image processing methods and systems for video signals, and more specifically, to image processing methods and systems providing video noise reduction and edge enhancement.
In image signal processing, reduction of noise and edge enhancement are two important processes. Video signal bandwidth is typically limited as the video signals are compressed by JPEG or MPEG for transmission. Compressed video signals can lose image edges or so called details of image as high frequency components of the signals are attenuated. Noise reduction usually involves averaging, suppression, or blurring, and edge enhancement usually involves an unsharp masking or Laplacian filter (or a high pass filter). Image processing methods for noise reduction usually entail smearing of details, whereas methods for edge enhancement usually enhance unwanted noise and edges simultaneously. The two processes are difficult to reconcile as the noise reduction process requires a further reduction of the video signal band and removal of high frequency components while the edge enhancement process requires increased high frequency components of the signals. A preferred solution is to discriminate noises from edges in image processing such that details can be preserved after noise reduction and only edges are enhanced in edge enhancement.
A video signal processing circuit disclosed in U.S. Pat. No. 5,926,577 performs noise reduction and edge enhancement without considering edge information in the noise reduction process, to reference to prevent details from smearing. Furthermore, noisy signals are provided to the input of the horizontal and vertical edge enhancement signal generation circuits, causing both noise and edge to be enhanced. In U.S. Pat. No. 5,757,977, a fuzzy logic filter detects edge directions and noise level, and selects a most probable edge direction for edge enhancement without discrimination between smooth areas and areas with edge. The strategy of choosing the most probable edge direction for edge enhancement may not be appropriate for each image area, since, for example, edge enhancement may readily enhance noise in image areas belong to smooth area.